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Volume 12 of W. Ross Ashby's Journal
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1949
Volume 12
2696+03 2696+04
Summary: Better definition of a system which shows extinction of its conditioned reflex. (Continued over)
2697 2698
The Conditioned Reflex [25]: Mechanism for conditioned reflex of second order, 2699.
Unsolved problems [7]: Can the secondary conditional reflex of 2699 be demonstrated?
Summary: A possible mechanism for conditioned reflexes of the second order.
Oddments [21]: A slight tendency in the central nervous system can easily be magnified to a large and complete change, 2700.
2699 2700
Summary: A slight tendency within the nervous system can easily be magnified to a maximal change in the effectors.
Arc algebra for arcs
Stimulus algebra of compound stimulus
Stimulus compound
2701 2702
Summary: We must distinguish in a conditioned reflex experiment between the pattern represented by the experimenter's controls and the pattern of what arrives at the cortex.
Summary: Example of preceeding section.
2703 2704
2705 2706
2707 2708
Summary: A system for relating stimuli given to arcs activated.
2709 2710
2711 2712
Natural Selection [8]: The effect of selection on the distribution of a statistic 2713.
Summary: The effects of selection on the distribution of a statistic.
2713 2714
Summary: Numerical example of the solution of [x'=Ax] by x=etAx0.
2715 2716
Laplace transformation example
Summary: Example of equations solved by Laplace transformations.
2717 2718
1950
Organisation number of
Organisation number of types of
2719 2720
Summary: An enumeration of the possible types of organisation. Summarised 2736
2721 2722
2723 2724
Summary: In a given absolute system, if n-1 variables follow a given line of behaviour and the initial state of the n-th is given, then the behaviour of the n-th is also determined. 5051
2725 2726
Summary: Predicting behaviour of unobservable variables. (Continued 2732)
2727 2728
Oddments [22]: Binary counters with feedback 2729.
2729 2730
Summary: Binary counters.
Oddments [23]: Another way of getting information about unobservable variables, 2732.
2731 2732
Summary: A new way of getting information about unobservable variables in an absolute system. 5051
Epistemology [4]: A way of getting information about unobserved variables 2734.
2733 2734
Summary: Examples.
Organisation number of
2735 2736
Summary: The ways of organising classified and tabulated.
2737 2738
2739 2740
Summary: Proof of an entry in the previous section.
Civil Service Greave's book
2741 2742
Feudal system civil service still is feudal system
Society [29]: Civil service, Greave's book on, feudal structure of, dispersion in, my suggestions for, 2743.
2743 2744
Summary: Organisation of a civil service. 2888, 2828, 4245
2745 2746
The Conditioned Reflex [26]: Conditioned reflex demonstrated on the homeostat, 2747, 2762.
2747 2748
Forcing a variable forcing homeostat
Homeostat shows conditioned reflex
Reflex, conditioned on homeastat
2749 2750
2751 2752
Summary: A conditioned reflex demonstrated on the homeostat. 2762, 5708, 5855
Substitution (mathematical) two simple examples
Summary: Examples of simple substitutions.
Mind (individual) meaning of
2753 2754
Summary: On the nature of 'mind'. (An application 2790)
Reflex, conditioned theory of
Oddments [24]: Behaviour of an absolute system when one variable is forced off its natural path, 2756.
2755 2756
2757 2758
2759 2760
Summary: Effect of diverting a variable from its path.
The Conditioned Reflex [26]: Conditioned reflex demonstrated on the homeostat, 2747, 2762.
2761 2762
Reflex, conditioned requires non-reinforcement
2763 2764
Summary: Conditioned reflex in ultrastable system regarded as change of resting state. 2855, 5855, 6745
Boolean algebra of relays
Relay Boole algebra of
Switching Boole algebra of
2765 2766
Summary: Fundamental theory of relays and Boole's algebra.
2767 2768
Summary: Emperical tests of the chance of stability collected to date.
2769 2770
Summary: Chance of stability. 3050
Higher geometry of fields and matrix theory [23]: If a number, positive or negative, is added to all non-diagonal elements, the system becomes unstable when the number is large enough, 2772.
2771 2772
Summary: Wholes whose stability differs entirely from those of the parts.
Equilibrium of [4-point dependency figure]
2773 2774
Summary: Joining unstable systems to form a stable one.
Equilibrium of [3-point dependency figure]
2775 2776
2777 2778
Higher geometry of fields and matrix theory [24]: Characteristic equation of MATRIX 2780.
2779 2780
Computing machines Berkeley's book on
2781 2782
Bit (= binary digit) quantities in speaking etc
Homeostat new possibility
Information quantitative examples
Delay (in substitution) and oscillation
Society [30]: Oscillations in fly population and its cause, 2784.
2783 2784
Code types of
Genes as information
Information in genes
2785 2786
Summary: Genetic inheritance as information. (See 2806)
Summary: Dictionary definitions: Absolute, Behaviour, Break, Critical.
Summary: Dictionary definitions: Disperse, Essential, Field, Independence, Interaction, Iterate, Parameter, Regular.
2787 2788
Summary: Dictionary definitions: Representative, Stability, State, System, Variable.
Activity variety of
Group (mathematical) scientific knowledge as
Epistemology [3]: An early review of what is meant by 'knowing' { 2790 - 2801 }
2789 2790
Constraint and natural law
Laws of nature discovery, and adaptation
Relation economy of
Epistemology [3]: An early review of what is meant by 'knowing' { 2790 - 2801 }
Summary: Discovering a scientific law is like an animal getting one reaction-system adapted to more than one environment. (Summary 2797)
Epistemology [3]: An early review of what is meant by 'knowing' { 2790 - 2801 }
2791 2792
Summary: A set of numerical values can be, in variables, an operand, and in parameters, an operator. (See next section)
Epistemology [3]: An early review of what is meant by 'knowing' { 2790 - 2801 }
Epistemology [3]: An early review of what is meant by 'knowing' { 2790 - 2801 }
2793 2794
Epistemology [3]: An early review of what is meant by 'knowing' { 2790 - 2801 }
Summary: The meaning of 'several' environments. (Amplified on 2801)
Epistemology [3]: An early review of what is meant by 'knowing' { 2790 - 2801 }
2795 2796
Epistemology [3]: An early review of what is meant by 'knowing' { 2790 - 2801 }
Epistemology [3]: An early review of what is meant by 'knowing' { 2790 - 2801 }
2797 2798
Epistemology [3]: An early review of what is meant by 'knowing' { 2790 - 2801 }
Epistemology [3]: An early review of what is meant by 'knowing' { 2790 - 2801 }
2799 2800
Summary: Groups and learning.
Science as adaptation
Epistemology [3]: An early review of what is meant by 'knowing' { 2790 - 2801 }
2801 2802
2803 2804
Summary: Examples of environments that can be divided into sub-environments.
2805 2806
Adaptation failures
2807 2808
2809 2810
2811 2812
2813 2814
Summary: A list of actions in which some object has to be avoided.
Summary: Some items of information theory.
Markov process / chain
Stochastic processes
Transition probability
2815 2816
Instinct, sex and hormones
2817 2818
Baudot code
Information in genes
Summary: Information theory.
Pattern (in general) recognition of
2819 2820
2821 2822
Group (mathematical) and pattern
Pattern (in general) as group-structure
Summary: Example of pattern and group.
Markov process / chain predicting words and letters
2823 2824
Summary: A stochastic process and information.
Stochastic processes
Psychiatric applications [9]: What happens when an animal is faced with a painful environment it cannot get away from, 2826.
2825 2826
Pain effect of unescapable pain
Summary: What a mammal does to an environment that cannot be adapted to.
2827 2828
Society [31]: Webb says that systems should not be able to control their own parameters and gives examples. 2829.
Summary: Social systems that can change their own parameters.
Personal notes [5]: Clifford Allbutt on a type of man, 2830.
2829 2830
Summary: Allbutt on a type of man.
Essential variables sometimes not related to critical states
Critical surface if not related to essential variables
Pain patient insensitive to pain
2831 2832
Summary: Description of a child lacking a sense of pain and often injured.
Learning improves with practice
2833 2834
2835 2836
2837 2838
Insight my solution of learning with 'insight'
Natural Selection [11]: All improvement in performance is, by my theory, to be obtained only by elimination of the bad. We look, therefore, not for the good to be developed but for the bad to be removed 2839.
2839 2840
Oddments [25]: Learning 'with insight' shown by a modified homeostat. 2841.
Summary: Solution of Harlow's problem.
2841 2842
Expectation effect on learning
Unsolved problems [8]: Expectation in the human directs learning: experiment demonstrating this; inexplicable. 2843.
The Conditioned Reflex [27]: When considering the conditioned reflex, consult Woodworth's book, which contains much material extra to Pavlov's, 2844.
2843 2844
Maze maze solving
The Conditioned Reflex [28]: Since the decerebrate dog still has abundant dynamic mechanisms, but cannot develop the more intricate reflexes, we can deduce that the intricate reflexes demand specialised mechanisms only to be found in the cortex. 2845, 2858.
Unsolved problems [9]: Transfer of training, from say one hand to the other, is not yet well explained 2846.
2845 2846
Summary: Modern psychology and my theory.
Insight Woodworth on
Summary: How to 'prove' a theory of the conditioned reflex.
The Conditioned Reflex [29]: Three ways of 'proving' that a theory of the conditioned reflex is true, 2848.
2847 2848
Pattern (in general) recognition of
2849 2850
Environment splitting environment
The Multistable System [10]: Experimental method of splitting an environment into parts, 2851.
2851 2852
Effect, law of notes on
The Conditioned Reflex [30]: Hebb points out that Pavlov's theory is contradicted by Pavlov's own facts, 2853.
Summary: Extracts from Hebb's book.
Personal notes [6]: Handicaps I have been spared, 2854.
2853 2854
Delay (in substitution) and sun-burn
The Conditioned Reflex [31]: A mechanism to be considered 2855.
Effect, law of notes on
2855 2856
Summary: A paper to be returned to later.
The Conditioned Reflex [28]: Since the decerebrate dog still has abundant dynamic mechanisms, but cannot develop the more intricate reflexes, we can deduce that the intricate reflexes demand specialised mechanisms only to be found in the cortex. 2845, 2858.
2857 2858
Summary: Conditioned reflex without cortex.
Summary: Razran's article.
The Conditioned Reflex [32]: Conditioned reflex in Carchesium, 2860.
2859 2860
Summary: A stimulus contains, in addition to its obvious content, derived and integrated components. (Not so much the stimulus contains them as that it will affect the nervous system as if it did) This is the principle: the 'stimulus' contains everything the nervous system can transform it into. Futile, therefore, is it to worry much about the exact details of the presentation. (Continued 2878)
Stimulus nature of
Summary: A process, in natural selection, that cannot reach a steady state but moves like the Flying Dutchman.
Natural Selection [32]: Predators tend to diverge from the usual appearance. This process has no resting state 2862.
2861 2862
Cause meaning tested
2863 2864
2865 2866
2867 2868
2869 2870
2871 2872
2873 2874
2875 2876
Summary: An empirical test on 30 cases of whether my definition of dependence agrees with what is understood by 'causation'. 5118, 3679, 3709
2877 2878
Summary: A 'stimulus' is not what it seems to be. It is all that happens between the experimenter and the depths of the subject's brain. 2896
2879 2880
Oddments [26]: Stentor has one rule for reacting to light; how this works out 2881.
2881 2882
Reflex and mechanism
Summary: A popular misunderstanding of what 'mechanistic' means.
2883 2884
Pattern (in general) recognition of
2885 2886
Summary: Correspondence of primative animal to machine, and object recognition.
Society [32]: Control by target-setting, 2887.
Summary: Social cybernetics. 2898
2887 2888
Summary: Part-environment relation in the Multistable System. 4193
The Multistable System [11]: In the multistable system each arc does not test itself against its environment but the whole against the whole, 2889.
Summary: Example of multistable system.
Unsolved problems [10]: A calculus is wanted to handle variables in their activations, 2890.
2889 2890
Reducibility example in pattern
The Multistable System [12]: Example, in perception, of the multistable system adapting in parts, 2891.
2891 2892
2893 2894
Reflex reflex behaviour, meaning of
Summary: Comments on the books. Examples of part-functions.
Stimulus nature of
2895 2896
Unsolved problems [11]: Cannot the 'experimenter' who injects disturbances be replaced by a more 'natural' phenomenon? 2897.
Society [33]: Can all legislative activities be reduced to the setting of targets? 2898.
2897 2898
Personal notes [7]: My theory breaks up the old concepts and replaces them by new constructions; list of examples, 2899.
Summary: The new point of view.
2899 2900
2901 2902
Summary: Axiomatic basis of the canonical equations, preliminary.
2903 2904
Natural Selection [31]: Fixity itself provides the means by which the fixity can be overthrown. All is movement 2906.
Society [34]: Animal populations fluctuate incessently and their characteristics are always on the change. There is no resting state. 2906.
2905 2906
Summary: I have little to learn from what is known of ecological systems.
2907 2908
2909 2910
2911 2912
Summary: Canonical equations of a regular system. See 2922
The Conditioned Reflex [33]: Effect of alternate reinforcement and non- reinforcement: 2914.
2913 2914
Personal notes [8]: I am carefully avoided, 2915.
2915 2916
Environment for survival
Part-function Eddington on
Quotations [11]: Quotation by Eddington on the distribution of part-functions, 2917.
Absolute system transition test
Transition probability
2917 2918
2919 2920
Summary: Defining and testing an absolute system.
2921 2922
2923 2924
Summary: On the canonical equations of a regular system
Gestalt recognition
Invariant collected notes
Pattern (in general) recognition of
2925 2926
2927 2928
Summary: Some collected notes on pattern or class-recognition, and invariants.
The Conditioned Reflex [34]: See notes from Gantt, 2930.
2929 2930
Unsolved problems [12]: The bee that wanders from its hive and returns, 2931.
2931 2932
Summary: A simple form of motor equivalent. (See 2939)
2933 2934
Summary: 'Two-stage' ultrastability.
2935 2936
2937 2938
2939 2940
2941 2942
2943 2944
2945 2946
2947 2948
Summary: Essay on 'motor equivalents.' See also 2989.
DAMS (Dispersive and Multistable System) [3]: How to design and build a multistable system. 2950. Its value basis, 2953.
Personal notes [9]: Origin of the second machine 2950.
2949 2950
Summary: A new principle for a new machine.
Summary: Law relating the lingering of the representative point with the density of critical states.
Ergodism and ultrastability
Ultrastability density of critical states
2951 2952
DAMS (Dispersive and Multistable System) [3]: How to design and build a multistable system. 2950. Its value basis, 2953.
Summary: Elementary features of my new machine. (See 2955) (changed to 3042)
Neon lamp
Part-function given by value
2953 2954
Essential variables relation to multistable system
DAMS (Dispersive and Multistable System) [73]: Another form, with the essential variables' limits separate from the step-functions', 2955.
2955 2956
The Multistable System [100]: Discriminative feedback from essential variables. 2958.
2957 2958
Environment relation to essentail variables
Essential variables relation to environment
2959 2960
2961 2962
Neuron maximal value of
Psychiatric applications [12]: The value of each unit if used with maximal efficiency, 2964.
2963 2964
2965 2966
2967 2968
The Multistable System [98]: The most efficient way is to make the environment show the specific step-functions that are to be altered 2970.
2969 2970
2971 2972
Summary: Multistable systems, essential variables, dispersion, how to alter step-functions selectively.
2973 2974
2975 2976
Summary: Behaviour of systems of part-functions.
The Multistable System [102]: Systems of part-functions, to be stable, must have intrinsic stability. 2978.
2977 2978
DAMS (Dispersive and Multistable System) [7]: DAMS' intrinsic stability, 2979, 2982, 3050.
Summary: Intrinsic stability: general, and of my new machine.
2979 2980
DAMS (Dispersive and Multistable System) [7]: DAMS' intrinsic stability, 2979, 2982, 3050.
2981 2982
Summary: The equations of the new machine, (See next page) Confirmed 2990
DAMS (Dispersive and Multistable System) [8]: DAMS, equations of, 2983. DAMS Mark 13, equations of, 3053.
Summary: Chance in my machine that n active variables are stable.
DAMS (Dispersive and Multistable System) [11]: Probability that k active variables in DAMS will be stable, 2984.
2983 2984
Oddments [27]: The intrinsic stability of neurons is high, 2985.
Summary: Intrinsic stability of brain and my new machine. 4154
Oddments [35]: In the brain, the combination of high intrinsic stability with powerful amplification gives speedy action, 2986.
2985 2986
Non-linear systems Stoker on
Group (mathematical) use of characteristics
The Multistable System [96]: Dispersion must first occur in a memory-free region if one reaction is not to upset another. 2988.
2987 2988
Summary: Sensory (dispersive) cortex must contain no learning mechanisms.
Cortex, visual must contain no memory
Receptors and sensory cortex must contain no learning apparatus
Chasing equation of
Coding in machine
Output as function of input
Transformation function-forming
2989 2990
Summary: Canonical equations of systems composed of units each of which tries to make itself (its dial value) some function of the others. (3200)
Society [35]: Equations of a society in which each unit tries to maintain itself at some function of its surroundings 2991.
Summary: The system that does not generate information is identical with an absolute system. 3032
Information the noiseless system
Oddments [28]: Is the absolute system 'noiseless'? 2992, 3013, 3031, 3060.
2991 2992
Summary: Redundancy and information.
Markov process / chain examples
Memory sentence with short memory
Redundancy organisms prefer highly redundant information
Sentence with limited memory
The Multistable System [15]: Human beings like information to be highly redundant: does this link with replication in multistable systems? 2993.
2993 2994
Summary: For training, essential variables are not necessary. (See 3003)
2995 2996
2997 2998
Summary: Serial training in the machine. (See 3004)
Summary: Note on the 'principle of continuity'.
Continuity principle of continuity
2999 3000
Summary: A display for the new machine.
DAMS (Dispersive and Multistable System) [4]: Display for DAMS, 3001.
Summary: A simple and well known example of a system of part-functions.
Part-function heap of twigs
3001 3002
3003 3004
Summary: Serial learning.
Homeostat equations etc
3005 3006
Summary: Canonical equations of the homeostat.
Effect, law of Skinner demonstrates
The Multistable System [13]: Skinner's experiments showing how arcs interact, 3008.
3007 3008
Memory long duration of
3009 3010
The Conditioned Reflex [35]: Extinction is not complete if the conditions are changed 3011.
3011 3012
Summary: Facts on learning.
Summary: Absolute system conserves information.
Oddments [28]: Is the absolute system 'noiseless'? 2992, 3013, 3031, 3060.
The Multistable System [14]: Discussion of how the multistable system adapts, 3014.
3013 3014
The Multistable System [17]: Adaptive behaviour, in the multistable system, is built out of scrap; it is the environment that enforces the perfection. 3015.
The Multistable System [37]: The multistable system must progress in adaptation by additive increments, like the genes. 3016.
3015 3016
3017 3018
Summary: Multistable system gives partly additive responses. A reaction pattern can be 'strengthened' by noisy variation of parameters. 4155
Noise may improve multistable systems
The Multistable System [38]: The deliberate injection of noise into a multistable system may improve its performance in some specific learning. 3019.
Equilibrium 'difficulty' of
3019 3020
Summary: A better meaning for 'difficulty of finding stability.'
The Multistable System [103]: A system of part-functions with k active is as difficult to stabilise as one of k full-functions 3022.
3021 3022
3023 3024
Summary: n part-functions of which k are active at any one time is as easy to stabilise as k, not n, full-functions.
The Multistable System [99]: Relation of the multistable system to its environments. 3082, 3026.
3025 3026
Summary: A multistable system adapting to several environments.
3027 3028
3029 3030
Summary: Necessary and sufficient conditions that a first adaptation should be still present after a second has taken place.
Oddments [28]: Is the absolute system 'noiseless'? 2992, 3013, 3031, 3060.
Information the noiseless system
3031 3032
Summary: The noiseless transducer is the absolute system.(Continued 3164)
3033 3034
Summary: Theorem on absolute systems. Continued next page.
3035 3036
Summary: Theorem on absolute systems. Here is the theorem in its final form for proving step-functions...
Step-mechanism deduced
3037 3038
Receptors information enters only via receptors
Personal notes [10]: The book written 3039.
3039 3040
Summary: Systems of part-functions automatically provide step-function. (N.B. This need further investigation and more rigorous formulation).
DAMS (Dispersive and Multistable System) [6]: DAMS, final placements of neons 3042.
3041 3042
Summary: Mark 13 DAMS works.
DAMS (Dispersive and Multistable System) [9]: DAMS has a higher order stability in 'number of neons lit' 3043.
Summary: Stability in the system 'number of neons lit'.
3043 3044
3045 3046
Summary: Joining 'at random'.
3047 3048
Amplifier and stability
Equilibrium effect of amplifier
DAMS (Dispersive and Multistable System) [7]: DAMS' intrinsic stability, 2979, 2982, 3050.
3049 3050
3050+01 3050+02

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